期刊論文
| 學年 | 110 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2021-10-30 |
| 作品名稱 | Investigating online social media users' behaviors for social commerce recommendations |
| 作品名稱（其他語言） | |
| 著者 | Liao, S.H.; Widowati, R.; Hsieh Y.C. |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | Technology in Society 66, 101655 |
| 摘要 | Online social media create virtual communities and network platforms that people use to create, share, and exchange opinions, views and experiences. With social networks, social commerce not only relies on commerce, but online social media can also promote the sale of goods or services online. Many online operators have begun to use recommendation systems to analyze customer purchase history and identify individual products that customers may purchase. This enables the company to send product information to consumers to attract their attention. In addition, consumers have a higher purchase rate for recommended products based on consumer data. Based on a survey in Taiwan society, this study uses the questionnaire survey method to collect data on a relational database. This study investigates Taiwan online social media users’ behaviors using data mining methods, including clustering analysis and association rules. Clustering analysis is to investigate possible profiles of users and association rules are to find knowledge patterns and rules of user profiles, online social media usage motivation/preferences and social commerce behavior in order to generate social commerce recommendations in terms of social technology development in the modern society. |
| 關鍵字 | Online social media;Social commerce;Electronic commerce;Data mining;Knowledge discovery;Recommendation systems |
| 語言 | en_US |
| ISSN | 0160-791X |
| 期刊性質 | 國外 |
| 收錄於 | SSCI Scopus |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 是 |
| 國別 | GBR |
| 公開徵稿 | |
| 出版型式 | ,電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/120938 ) |